Hi Pavan,

Thanks for proposing this. +1 from my side.

Best,
Przemek

On 2026/08/08 06:42:41 Pavankumar Gopidesu wrote:
> Hi Airflow community,
> 
> I would like to propose a new provider for Apache DataFusion:
> apache-airflow-providers-apache-datafusion.
> 
> Background:
> 
> During the AIP-99 (common.ai) discussions, we agreed to use Apache
> DataFusion to support querying files on object stores. This functionality
> powers the SQLToolset and the LLM data-quality operators within common.ai,
> but the engine code currently lives inside the common.sql provider and only
> supports Amazon S3 and local files.
> 
> Proposal:
> 
> I propose moving the DataFusion functionality out of common.sql into a
> dedicated provider under providers/apache/datafusion, and extending it to
> support additional storage backends and file formats. This keeps common.sql
> focused on DB-API databases while giving DataFusion a dedicated home to be
> discovered, used, and extended independently.
> 
> Why DataFusion?
> 
>   - In-process, Arrow-native engine: Runs directly inside the worker
> without requiring an external service or cluster.
>   - Vectorized, streaming execution: Queries datasets larger than the
> worker's RAM efficiently.
>   - Built-in object store support: Straightforward extension to S3, GCS,
> Azure, and HTTP.
> 
> On a personal note, I use DataFusion daily to analyze datasets of over 50
> million rows on a single machine, which convinces me it is an excellent fit
> for Airflow.
> 
> Performance References:
> 
>   - ClickBench Benchmarks: DataFusion consistently ranks among the fastest
> single-node engines for querying Parquet files:
> https://benchmark.clickhouse.com/
>   - Version 54.0.0 Release (June 2026): Significant join, scan, and
> planning improvements:
> https://datafusion.apache.org/blog/2026/06/12/datafusion-54.0.0
>   - Dynamic Filters (September 2025): Up to 25x faster queries for common
> patterns: https://datafusion.apache.org/blog/2025/09/10/dynamic-filters
>   - SIGMOD 2024 Paper: Peer-reviewed reference on architecture and
> performance: https://dl.acm.org/doi/10.1145/3626246.3653368
> 
> Regards,
> Pavan
> 

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